Study and Improvements in Landmarks Extraction in 2D Range Images Based on an Adaptive Curvature Estimation

Certad, Novel; Acuña, Raul; Terrones, Angel; Ralev, Dimitar; Cappelletto, José; Grieco, Juan C.

doi:10.1109/andescon.2012.31

Cited by 5 publications

(2 citation statements)

References 5 publications

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“…Various distance threshold calculation approaches have been proposed in the literature [23]. The most common approach is to introduce a fixed threshold value which must be maintained at every situation.…”

Section: Obstacle Closest Distancementioning

confidence: 99%

Adaptive Collision-Free Reaching Skill Learning from Demonstration

Ogenyi

Zhou

et al. 2020

Communications in Computer and Information Science

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In this paper, we considered the task of the robot learning low-level trajectory task in a novel clustered constraint environment.We propose a novel adaptive trajectory algorithm used to generate the necessary trajectory which satisfies the constraint of avoiding collision with an obstacle. Our approach is based on Gaussian mixture model which decomposes the trajectory into several ellipses since the isoline of a single Gaussian model is also an ellipse. Moreover, we employed the principle of the artificial potential field to modify the direction of the motion in the presence of obstacles. Since our approach is based on the underlying reactive skill dynamics, it does not share the same disadvantages as approaches which assume both the model of the task trajectory and the response from the obstacle should be learned from the demonstrations.

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Section: Obstacle Closest Distancementioning

confidence: 99%

Adaptive Collision-Free Reaching Skill Learning from Demonstration

Ogenyi

Zhou

et al. 2020

Communications in Computer and Information Science

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“…The threshold value in their Adaptive Breakpoint Detector (ABD) method as well developed by Borges and Aldon [13]. They use auxiliary angles to determine the point of intersection and use it as a reference for the threshold value, and Certad et al [18] also adjusted the threshold value in the ABD. They modify the measurement distance value in the ABD equation with the shortest distance value from either the current or previous distance.…”

Section: Introductionmentioning

confidence: 99%

Development of Adaptive Line Tracking Breakpoint Detection Algorithm for Room Sensing using LiDAR Sensor

Amin¹,

Priandana²,

Hardhienata³

2022

IJACSA

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This research focuses on the use of Light Detection and Ranging (LiDAR) sensors for robot localization. One of the most essential algorithms in LiDAR localization is the breakpoint detector algorithm which is used to determine the corner of the room. The previously developed breakpoint detection methods have weaknesses, such as the Adaptive Breakpoint Detector (ABD), could generate dynamic threshold values. The ABD results, on the other hand, still require Line Extraction to obtain the corner breakpoint. Line Extraction method, e.g. IterativeEnd Point Fit (IEPF), is used to categorize data, resulting in the generation of a line pattern as an interpretation of a wall. The computational method for obtaining the corner breakpoint becomes longer as the line is extracted. To address this issue, our algorithm proposes a new threshold area in the form of an ellipse with the threshold value parameter obtained from previously identified room size and sensor characteristics. As a result the corner breakpoint detection becomes more adaptive. The goal of this research is to create an Adaptive Line Tracking Breakpoint Detector (ALTBD) approach that will reduce the computing time required to detect corner breakpoints. Furthermore, the Line Extraction method required for corner breakpoint detection is modified in the ALTBD. To distinguish between the edge of the wall and the corner of the room, the boundary value is increased. The ALTBD method was tested in a simulation arena comprised of multiple rooms and halls. According to the results, the ALTBD computation time is faster in detecting corner breakpoints than the ABD IEPF method, also the accuracy for determining the position of the robot was improved.

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